Statistical Consulting
on the Miami University Campus
The Statistical Consulting Center (SCC) offers statistical consulting
to faculty, staff, graduate and undergraduate students conducting research
at Miami University. The SCC is a group of statisticians who provide consultation
on all aspects of data collection, analysis and interpretation. The Center
is funded by the University to promote high quality statistical consulting
to researchers and is staffed by a Manager and full-time statistics faculty
in the Department of Mathematics and Statistics.
Consulting services will be provided free to Miami University students,
faculty and staff who have no external support, or on a cost recovery basis
to those with externally funded support. External projects are accepted
on a case by case basis and will be charged competitive rates.
How to Use the Center
Contact the SCC at the earliest possible stage of your research. We
recommend that potential clients contact the SCC at the earliest possible
stage of research planning and manuscript or grant preparation to help
ensure a successful statistical analysis. If you would like to discuss
your statistical design and analysis needs with the SCC, or if you need
additional information, call the Center at 529-5148 or
e-mail
the Manager to set up an appointment.
Services Provided by the
SCC
The SCC can play an effective role as a member of your research team,
providing valuable input and expertise in the analysis of your research
data. Specifically, we can assist in the following areas:
Proposal Preparation
The SCC is happy to assist you in the preparation of research proposals,
providing guidance in both the sizing of statistical studies and development
of methods section writeups.
Data Management
We can update or manipulate research data from any one of a number
of data or spreadsheet formats and can offer advice regarding how to structure
your data most effectively for analysis. We can also provide assistance
with many popular data analysis software applications.
Before the Analysis
We can assist you regarding the effective collection of your sample
data, designing your experiment or survey, and advising you regarding the
most appropriate statistical methodology for your data.
Data Analysis and Statistical Modeling
The SCC is fully qualified to provide you with data analysis capabilities
ranging from the most basic standard descriptive statistical techniques
to the most powerful modern inferential statistical methods. Areas of expertise
include:
Design of Experiments and Analysis of Variance (ANOVA)
Multiple Regression (including response surface methodology and robust
regression methods)
Generalized Linear Models (including logistic/probit/Poisson regression,
linear and non-linear mixed models)
Multivariate Data Analysis techniques
Biostatistics and Survival Analysis
Categorical Data Analysis
Nonparametric Statistics
Quality Control and Industrial Statistical Methods
Sample Survey Design Analysis
Exploratory Data Analysis (EDA)
Bayesian Methods
Computational Methods (including Monte Carlo simulation and bootstrap methods)
After the Analysis
Once your data have been analyzed, we will assist you in interpreting
analysis results into clear, understandable findings. SCC is also happy
to be involved in the preparation of research manuscripts for publication.
Computing Resources
Available
The SCC staff maintains expertise in many popular statistical analysis
software applications, including SAS, SPSS, R, S-Plus and Minitab. We also
provide data importation from a wide variety of data formats, including
Excel spreadsheets.
SCC Staff and Affiliated Faculty
-
Dr. Robert L. Schaefer
Ph.D., University of Michigan
Director of Statistical Consulting; Biostatistics, Linear Models
-
Michael R. Hughes
M.S., Miami University
SCC Manager and Consultant
-
Dr. A. John Bailer
Ph.D., University of North Carolina
Biostatistics, Quantitative Risk Estimation, Statistical Methods
for Environmental & Occupational Health
-
Dr. Robert Davis (Hamilton Campus)
Ph.D., University of Southwestern Louisiana
Statistical Process Control, Environmental Statistics
-
Dr. Charles Dunn
Ph.D., Texas A&M University
Statistics, Multivariate Analysis
-
Dr. Amy Fisher (Middletown Campus)
Ph.D., University of Cincinnati
Robust Statistics and Linear Regression
-
Dr. David J. Groggel
Ph.D., University of Florida
Nonparametric Statistics, Design of Experiments
-
Dr. Emily Murphree
Ph.D., University of North Carolina
Probability and Stochastic Processes, Regression Analysis
-
Dr. Robert Noble
Ph.D., Virginia Tech
Bayesian Statistics, Multivariate and Environmental Statistics
-
Dr. Douglas Noe
Ph.D., University of Illinois
Data Mining, Bayesian Methods
-
Dr. Kyoungah (Kay) See
Ph.D., Virginia Polytechnic Institute and State University
Sampling Designs, Principal Component Analysis, Environmental Toxicity
Studies
-
Dr. John Skillings
Ph.D., Ohio State University
Analysis of Variance, Nonparametric Statistics
-
Dr. Vasant Waikar
Ph.D., Florida State University
Multivariate Analysis
Page maintained by Michael Hughes.
This page was last updated on January 10, 2007.